Artificial Intelligence

Artificial intelligence (AI) is becoming a crucial component of healthcare to help augment physicians and make them more efficient. In medical imaging, it is helping radiologists more efficiently manage PACS worklists, enable structured reporting, auto detect injuries and diseases, and to pull in relevant prior exams and patient data. In cardiology, AI is helping automate tasks and measurements on imaging and in reporting systems, guides novice echo users to improve imaging and accuracy, and can risk stratify patients. AI includes deep learning algorithms, machine learning, computer-aided detection (CAD) systems, and convolutional neural networks. 

Revamped infrared spectroscopy may improve brain imaging

A new paper published in Neurophotonics details improvements made to near infrared spectroscopy (fNIRS)-based imaging that may enhance brain imaging research.

August 23, 2019

MRI scans reveal vascular damage caused by vaping

"These products are advertised as not harmful, and many e-cigarette users are convinced that they are just inhaling water vapor," said researchers in a recent article published by Radiology.

August 21, 2019

MS findings may guide future neuroimaging biomarkers

Grey matter atrophy impacts localized brain regions that are functionally connected in patients with multiple sclerosis (MS), according to a new study published in Clinical Radiology. The results may serve as a framework for developing imaging biomarkers.

August 19, 2019
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New technique pushes closer to real-time MRI brain imaging

A team of researchers backed by a division within the National Institutes of Health (NIH) has created a novel MRI technique that can image a thinking brain 60-times faster than traditional methods.

August 19, 2019

US global leader in publishing AI radiology studies

The United States published more AI-based radiology studies than any other country across the globe, according to a new analysis released Aug. 15 in the American Journal of Roentgenology.

August 16, 2019

AI trained on synthetic images makes accurate cancer diagnoses

A machine learning method trained on synthetic breast ultrasound elastography images accurately classified tumors when applied to real-world images, according to a new study published in the August issue of Computer Methods in Applied Mechanics and Engineering.

August 15, 2019

Repeated head hits cause brain damage regardless of concussions

A season of football can significantly damage a player’s brain, even if they did not experience a concussion. The results bolster evidence that suggests even repeated hits to the head can cause impactful brain damage.

August 14, 2019
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MRI reveals ‘smoldering’ brain spots may indicate severe MS

“We hope these results will help test the effectiveness of new therapies for this form of MS and reduce the suffering patients experience,” said lead author of the study published in JAMA Neurology.

August 14, 2019

Around the web

Two advanced algorithms—one for CAC scores and another for segmenting cardiac chamber volumes—outperformed radiologists when assessing low-dose chest CT scans. 

"Gen AI can help tackle repetitive tasks and provide insights into massive datasets, saving valuable time," Thomas Kurian, CEO of Google Cloud, said Tuesday. 

SCAI and four other major healthcare organizations signed a joint letter in support of intravascular ultrasound. 

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